Experience

Work History

Scalable data solutions, ML deployment, and cloud infrastructure across enterprise and growth-stage organizations.

Data Engineer

Greenphire LLC

Thoma Bravo portfolio company • Atlanta, GA

September 2023 – Present

Design, build, and maintain scalable data pipelines, ML models, cloud infrastructure, APIs, and visualization solutions for clinical trial operations.

Key Achievements

  • Delivered Patient Spend Budgeting solution on AWS
  • Built time series forecasting models (DeepAR, SageMaker)
  • Architected company-wide reporting framework
  • Translated legacy SQL ETL to PySpark on AWS Glue

Technologies

AWSPythonPySparkKubernetesTerraformFastAPIAngularQlik

Phirestarter Award Nominee

Software Engineer

Checkbook.io

San Mateo, CA

May 2022 – December 2022

Enhanced internal CMS performance and developed new features for digital check creation platform.

Key Achievements

  • Enhanced CMS performance using Gatsby and Netlify
  • Implemented address verification system
  • Upgraded frontend to React 18.10

Technologies

ReactAngularPythonGatsbyNetlifyJavaScript

Machine Learning Engineer Intern

SemiCab

Atlanta, GA

May 2021 – August 2021

Developed and evaluated ML models to forecast truck demand; DeepAR significantly outperformed traditional methods.

Key Achievements

  • Developed ML models (MA, SES, Holt-Winters, SARIMA, DeepAR)
  • Identified DeepAR as most effective model
  • Deployed DeepAR on AWS SageMaker

Technologies

PythonAWS SageMakerFlaskDeepAR

Computer Science Summer Institute

Google

Atlanta, GA

July 2019 – August 2019

Developed full-stack web app aggregating real-time inventory data from multiple merchants using Google APIs.

Key Achievements

  • Full-stack web app with Google APIs
  • Dynamic product comparison interface
  • Team collaboration

Technologies

JavaScriptHTMLCSSGoogle APIs

Big Data Intern

Cardlytics

Atlanta, GA

May 2018 – August 2018

Developed scalable data pipelines to process real-time consumer purchase data for targeted marketing.

Key Achievements

  • Scalable data pipelines for real-time processing
  • Optimized batch/streaming queries with Kafka and Spark
  • ETL workflows with Spark/Scala

Technologies

ScalaSparkKafkaHadoopVertica